Using machine learning models to predict oxygen saturation following ventilator support adjustment in critically ill children: A single center pilot study-Reference-Cited by-同舟云学术

Using machine learning models to predict oxygen saturation following ventilator support adjustment in critically ill children: A single center pilot study

Published:2019-02-20 Issue:2 Volume:14 Page:e0198921
ISSN:1932-6203
Container-title:PLOS ONE
language:en
Short-container-title:PLoS ONE

Author:

Ghazal Sam,Sauthier Michael^ORCID,Brossier David^ORCID,Bouachir Wassim,Jouvet Philippe A.^ORCID,Noumeir Rita

Funder

Fonds de Recherche du Québec - Santé

Ministère de la Santé et Services Sociaux du Québec

Sainte-Justine University Hospital

Institut de Valorisation des données de l'Université de Montréal

Natural Sciences and Engineering Research Council of Canada

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference26 articles.

1. Development and implementation of explicit computerized protocols for mechanical ventilation in children;P Jouvet;Annals of intensive care,2011

2. Automated versus non-automated weaning for reducing the duration of mechanical ventilation for critically ill adults and children: a cochrane systematic review and meta-analysis;L Rose;Crit Care,2015

3. A pilot prospective study on closed loop controlled ventilation and oxygenation in ventilated children during the weaning phase;P Jouvet;Crit Care,2012

4. Simulations for mechanical ventilation in children: review and future prospects;O Flechelles;Crit Care Res Pract,2013

5. Creating a High-Frequency Electronic Database in the PICU: The Perpetual Patient;D Brossier;Pediatr Crit Care Med,2018

Cited by 31 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Clinician’s Guide to Understanding Bias in Critical Clinical Prediction Models;Critical Care Clinics;2024-10

2. Advancing ICU patient care with a Real-Time predictive model for mechanical Power to mitigate VILI;International Journal of Medical Informatics;2024-09

3. Prediction and simulation of PEEP setting effects with machine learning models;Medicina Intensiva;2024-04

4. Innovative Predictive Approach towards a Personalized Oxygen Dosing System;Sensors;2024-01-24

5. Sectionalized Self-Triggered Control for AUVs With Deferred Quantitative Constraints;IEEE Transactions on Instrumentation and Measurement;2024